Evidence map›Paper›PMID 29912282›Full record

ArticleBioinformatics (Oxford, England)2018

gmxapi: a high-level interface for advanced control and extension of molecular dynamics simulations.

M Eric Irrgang, Jennifer M Hays, Peter M Kasson

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Adaptive ensemble simulations of biomolecules.Current opinion in structural biology · 2018
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

M Eric IrrgangDepartment of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA.
Jennifer M HaysDepartment of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA.
Peter M KassonDepartment of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA.

Funding

Hardening and Development of the GROMACS Molecular Simulation EngineR01GM115790 · NIGMS · UNIVERSITY OF VIRGINIA · PI KASSON, PETER M, SHIRTS, MICHAEL R · 2016 to 2020
$1.1M
NIGMS NIH HHS R01 GM115790
6 · The paper itself

Abstract

Summary: Molecular dynamics simulations have found use in a wide variety of biomolecular applications, from protein folding kinetics to computational drug design to refinement of molecular structures. Two areas where users and developers frequently need to extend the built-in capabilities of most software packages are implementing custom interactions, for instance biases derived from experimental data, and running ensembles of simulations. We present a Python high-level interface for the popular simulation package GROMACS that i) allows custom potential functions without modifying the simulation package code, ii) maintains the optimized performance of GROMACS and iii) presents an abstract interface to building and executing computational graphs that allows transparent low-level optimization of data flow and task placement. Minimal dependencies make this integrated API for the GROMACS simulation engine simple, portable and maintainable. We demonstrate this API for experimentally-driven refinement of protein conformational ensembles. Availability and implementation: LGPLv2.1 source and instructions are available at https://github.com/kassonlab/gmxapi. Supplementary information: Supplementary data are available at Bioinformatics online.

Indexed as

Molecular Dynamics SimulationProtein FoldingSoftwareComputational BiologyComputer SimulationKineticsProtein Conformation

Identifiers

PMID29912282
PMCPMC6223363

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.